Google Cloud Platform Data Architect/Lead

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Sr Google Cloud Platform Architect

Location- NJ onsite. -

Sr positions must have 15 years exp and onsite NJ

Job Summary:

We are seeking a skilled Google Cloud Platform (Google Cloud Platform) Data Engineer to design, build, and optimize data pipelines and analytics solutions in the cloud. The ideal candidate must have hands-on experience with Google Cloud Platform data services, strong ETL/ELT development skills, and a solid understanding of data architecture, data modeling, data warehousing and performance optimization.

Key Responsibilities:

•   Develop ETL/ELT processes to extract data from various sources, transform it, and load it into BigQuery or other target systems.
•   Build and maintain data models, data warehouses, and data lakes for analytics and reporting.
•   Design and implement scalable, secure, and efficient data pipelines on Google Cloud Platform using tools such as Dataflow, Pub/Sub, cloud run, Python and linux scripting.
•   Optimize BigQuery queries, manage partitioning and clustering, and handle cost optimization.
•   Integrate data from on-premise and cloud systems using Cloud Storage, and APIs.
•   Work closely with DevOps teams to automate deployments using Terraform, Cloud Build, or CI/CD pipelines.
•   Ensure security and compliance by applying IAM roles, encryption, and network controls.
•   Collaborate with data analysts, data scientists, and application teams to deliver high-quality data solutions.
•   Implement best practices for data quality, monitoring, and governance.
  
  

Required Skills and Experience:

•   Bachelor’s degree in Computer Science, Information Technology, or related field.
•   Minimum 8 years of experience in data engineering, preferably in a cloud environment.
•   Minimum 3 years of hands-on and strong expertise in Google Cloud Platform services:
  
  

o  BigQuery, Cloud storage, Cloud run, Dataflow, Cloud SQL, AlloyDB, Cloud Balancer, PubSub, IAM, Logging and Monitoring.

•   Proficiency in SQL, Python and Linux scripting.
•   Prior experience with ETL tools such as Datastage, Informatica, SSIS
•   Familiarity with data modeling (star/snowflake) and data warehouse concepts.
•   Understanding of CI/CD, version control (Git), and Infrastructure as Code (Terraform).
•   Strong problem-solving and analytical mindset.
•   Effective communication and collaboration skills.
•   Ability to work in an agile and fast-paced environment.
•   Google Cloud Platform Professional Data Engineer or Cloud Architect certification is a plus.